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authornunzip <np.scarh@gmail.com>2019-03-08 18:30:14 +0000
committernunzip <np.scarh@gmail.com>2019-03-08 18:30:14 +0000
commit97cc07ebc57a813f1fd4b32f314f455c033ab55a (patch)
treec0c1fc60d55baf0bfc3b62962f714290ea7bb321 /lenet.py
parent240be62b504dbdcb0cadcaf313d111eefe9ceea0 (diff)
downloade4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.tar.gz
e4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.tar.bz2
e4-gan-97cc07ebc57a813f1fd4b32f314f455c033ab55a.zip
Remove get_lenet_pen
Diffstat (limited to 'lenet.py')
-rw-r--r--lenet.py13
1 files changed, 0 insertions, 13 deletions
diff --git a/lenet.py b/lenet.py
index 39a5cd7..3d388de 100644
--- a/lenet.py
+++ b/lenet.py
@@ -83,19 +83,6 @@ def get_lenet_icp(shape):
model.add(Dense(units=10, activation = 'relu'))
return model
-def get_lenet_pen(shape):
- model = keras.Sequential()
- model.add(Conv2D(filters=6, kernel_size=(3, 3), activation='relu', input_shape=(32,32,1)))
- model.add(AveragePooling2D())
-
- model.add(Conv2D(filters=16, kernel_size=(3, 3), activation='relu'))
- model.add(AveragePooling2D())
- model.add(Flatten())
-
- model.add(Dense(units=120, activation='relu'))
- model.add(Dense(units=84, activation='relu'))
- return model
-
def plot_history(history, metric = None):
# Plots the loss history of training and validation (if existing)
# and a given metric